We have now assessed a significant number of patients and DERM has correctly identified over 2,200 cancers. In our most recent quarterly performance review (Q4 2022-23), we saw that DERM found 99% of the cancers we have assessed while identifying over 3 in 4 benign lesions. The performance of DERM is consistently above the targets set by our Clinical Advisory Committee which are set based on clinical performance published in the literature.
It is important to note that no clinician or test is ever 100% accurate. DERM is no exception, though we are performing at a very high standard and continually strive to improve to the benefit of our patients.
You can see our latest and historical quarterly performance results on our Clinical Performance page.
In the majority of deployments DERM is deployed to assess patients after they have been referred by their GP. It is therefore not possible to directly reduce the number of referrals, however around 6% of 2ww referrals are skin cancer, above the rate GPs are generally targeted for cancer which is around 4%.
It’s not clear that reducing 2ww referrals should be the focus. DERM can effectively reduce the number of dermatologist appointments required for the volume of 2ww referrals.
At the time of writing, our latest performance report (Q4 2022-23) showed that DERM found 99% of skin cancers. Combined with use of the Skin Analytics teledermatology platform, our NHS Secondary Care partners remove the need for more than 64% of face-to-face two-week-wait appointments.
In addition to the data we publish, much of which has been externally audited, Skin Analytics is working with a number of external partners to evaluate and support the expansion of our services across the NHS. An example of some of this work is outlined below.
Unity Insights has been appointed by the NHS AI Lab to independently evaluate Skin Analytics. Unity Insights have completed an interim analysis and are due to publish a detailed report later this year.
The University of Exeter are working to independently evaluate our recently granted project through the SBRI Cancer Programme that will focus on the use of DERM in populations who have not been referred by their GP.
Researchers at The University of Birmingham involved with the creation of the Medical Algorithmic Audit framework published in the Lancet and the BMJ journals have been applying this framework to a Skin Analytics deployment. Results are expected later this year and will be made available to the NHS.
Edge Health are working on behalf of the East Midlands Academic Health Science Network to evaluate our pathway at University Hospitals Leicester with a report due end 2023. You can see a case study of the pathway previously conducted here.
DERM has been deployed since 2020 and over this time we have been monitoring post-deployment performance as part of our post market surveillance. Over this time we have seen over 50,000 patients in our NHS pathways and have demonstrated that our services are accessible to patients from a wide range of ages (18-100) and all skin types (Fitzpatrick I-VI).
It is well recognised that skin cancer is more prevalent in lighter skin types and so this is also reflected in the patient population which we have seen presented to our pathways. 3% of cases NHS organisations have seen with the Skin Analytics platform have been recorded as having Fitzpatrick type V/VI skin.
For these patients, we have correctly identified all cancers but the numbers are too low to report. We continue to monitor this closely with our NHS partners and are committed to building a solution for all patients.
Skin Analytics AI as a Medical Device (AIaMD), DERM, enables images to be captured in imaging hubs in locations more convenient to patients which can increase access to care. We are working with our NHS partners in the SBRI Cancer Programme to evaluate if the use of DERM allows for increased access to skin cancer assessments in populations that typically lack access to GP care (e.g. the homeless).
We have completed and regularly update our NHS England and NHS Improvement (NHSEI): Equality and Health Inequalities Impact Assessment (EHIA). To see our latest version, please contact us.
AI used in skin cancer pathways are medical devices governed by law under The UK Medical Device Regulations 2002 (“UK MDR”) which is overseen by the MHRA, the UK’s medicines and healthcare products regulatory agency.
DERM has the required UKCA mark as a Class IIa medical device under UK law and remains the only approved Class IIa device for assessing skin cancer.
Medical device regulation requires that manufacturers like Skin Analytics identify the benefits and risks to patients and provide sufficient evidence that residual risks are sufficiently low and outweighed by the benefits of the medical device.
The classification of medical devices under the UK MDR is a risk-based system taking into account the intended use and potential risks associated with a medical device. This approach uses a set of ‘classification rules’ to determine the appropriate classification for a device and, in turn, indicate the level of regulatory control and oversight required for the device.
Our AI product is classified as a Class IIa medical device. This means that our device is required to undergo a comprehensive quality and technical assessment by an independent body appointed by the MHRA to determine whether the device is compliant with the UK MDR. A key component of this assessment is the independent review of our Clinical Evaluation Report (“CER”).
The CER is a report that identifies, appraises and evaluates clinical evidence for a device in order to verify the safety and performance, including clinical benefits, of the device when used as intended. Skin Analytics has successfully completed this rigorous assessment and our device remains the only Class IIa approved AI medical device in dermatology.
Securing a Class IIa medical device approval is not a milestone, it is a commitment to continue to operate an effective quality management system that is evaluated against the best in class standards agreed by regulatory bodies.
That means that we are constantly working to maintain our medical device and operate safe and effective processes. It is a living process and one in which we are constantly looking for improvement.
AI as a medical device should be held to high standards and that is what the regulatory requirements do both with respect to clinical evidence and as importantly the quality and safety systems a company operates.
No, DERM does not self learn and while we continually improve our models and performance these are manually released following the appropriate regulatory pathway to ensure the appropriate verification and validation before release.
